Intention to learn differentially affects subprocesses of procedural learning and consolidation: Evidence from a probabilistic sequence learning task

Abstract

Procedural memory facilitates the efficient processing of complex environmental stimuli and contributes to the acquisition of automatic behaviours and habits. Learning can occur intentionally or incidentally, yet, how the mode of learning affects procedural memory is still poorly understood. Importantly, procedural memory is a complex cognitive function composed of different subprocesses, including the acquisition and consolidation of statistical, frequency-based and sequential, order-based knowledge. Therefore, we tested how statistical and sequence knowledge develops during incidental versus intentional procedural memory formation and during consolidation. Seventy-four young adults performed either the uncued, incidental (N = 37) or the cued, intentional (N = 37) version of a probabilistic sequence learning task. Performance was retested after a 12-hour offline period, enabling us to test the effect of sleep on consolidation; therefore, half of the participants slept during the delay, while the other half had normal daily activity (PM-AM versus AM-PM design). The mode of learning (incidental versus intentional) had no effect on the acquisition of statistical knowledge, while intention to learn increased sequence learning performance. Consolidation was not affected by intention to learn: Both statistical and sequence knowledge was retained over the 12-hour delay, irrespective of the mode of learning and whether the delay included sleep or wake activity. These results suggest a time-dependent instead of sleep-dependent consolidation of both statistical and sequence knowledge. Our findings could contribute to a better understanding of how the mode of learning (intentional or incidental) affects procedural memory formation and consolidation.

Deconstructing Procedural Memory: Different Learning Trajectories and Consolidation of Sequence and Statistical Learning

“…These observations support the interpretation that explicit instructions and the motivation to learn can have an overarching effect in that not only the instructed sequential but also the uninstructed statistical regularities can be learned more quickly. Interestingly, a recent study showed that, if the task is fix-paced instead of self-paced, no such overarching effect can be observed, suggesting a complex interplay of multiple factors that may influence the effect of explicit instructions on learning (Horváth et al, 2018). Further studies should directly test these factors.…”

Regularity extraction under stress: boosted statistical learning but unaffected sequence learning

“…As typical response times are under 500 ms, the fast pace of the task makes it unlikely that explicit sequence knowledge would have an impact on participants' RTs. Therefore, the consciously accessible knowledge of the sequence (reflected by the post-block sequence report score) and sequence learning (reflected by the RTs) seems to be dissociable measures (Horváth et al, 2019). The sequence report may be considered as a more explicit measure of sequence knowledge, while the sequence learning RT scores may serve as an implicit measure of sequence acquisition, even in an intentional learning condition.…”

“…We divided each participants' raw RT values of each trial type and each epoch by their own average performance of the first epoch of the task (for a similar approach, see Nitsche et al, 2003;Horváth et al, 2019), then we multiplied these values by 100 for easier presentation and interpretability. Participants' performance was around 100 at the beginning of the task and changed as the task progressed.…”

Skill learning can be independent of speed and accuracy instructions

“…After that, participants were asked to generate new sequences which are different from the learned one (exclusion condition). Both parts consisted of four runs, and each run finished after 24 button presses, which is equal to three rounds of the eight-element alternating sequence (Horvath, Torok, Pesthy, Nemeth, & Janacsek, 2018;Kiss, Nemeth, & Janacsek, 2019;Kobor et al, 2017). The successful performance in the inclusion condition can be achieved by solely implicit knowledge (however, explicit knowledge can also boost performance, but it is not necessary to the successful completion of the task).…”

“…To test whether the participants gained consciously accessible triplet knowledge, we calculated the percentage of the generated high-probability triplets in the inclusion and in the exclusion condition separately and tested whether it differs from the probability of generating them by chance. We also compared the percentages of the high-probability triplets across conditions (inclusion and exclusion task) and across groups (Accuracy Group and Speed Group) (for more details about the Inclusion-Exclusion task, see: Horvath et al, 2018;Kiss et al, 2019;Kobor et al, 2017).…”